Reservoir simulation system and method

ABSTRACT

The present disclosure describes an efficient process through which knowledge gleaned from prior reservoir simulations may be captured and applied to future simulations with or without user involvement. A plurality of reservoir simulation categories may be defined and stored to a database. In one embodiment, reservoir simulation data may be captured and analyzed in order to identify process steps and/or workflows for each category of stored reservoir simulations. Upon starting a new reservoir simulation, the system may identify the category of the simulation at issue and query the database in order to identify stored process steps and/or workflows applicable thereto. The stored process steps and/or workflows may then be applied to the new reservoir simulation automatically or by providing suggestions and/or recommendation to the user.

BACKGROUND

Oilfield operations generate a great deal of electronic data. Such datamay be used to access oilfield conditions and make decisions concerningfuture oilfield operations such as well planning, well targeting, wellcompletions, production rates, and other operations and/or operatingparameters. Often this information is used to determine when (and/orwhere) to drill new wells, re-complete existing wells, or alter oilfieldproduction parameters.

Oilfield data may be collected using sensors positioned about theoilfield. For example, sensors on the surface may monitor seismicexploration activities, sensors in the drilling equipment may monitordrilling conditions, sensors in the wellbore may monitor fluidcomposition, sensors located along the flow path may monitor flow rates,and sensors at the processing facility may monitor fluids collected.

Computer modeling and simulation of oilfield data is a vital componentof oil and gas exploration. Such systems typically conduct some form ofcomputational processing upon acquired or simulated oilfield data andthen export the processed data to one or more data visualizationapplication(s) for review by authorized personnel. Such systems may alsouse a color mapping structure to generate graphic visualizations ofacquired data in order to assist users in interpreting and analyzing theacquired data.

Known oilfield simulation platforms may require the reservoir engineerto build the initial model from scratch, enter/modify input parametersand then interpret the results based upon their individual experience.This process may be especially difficult for those users having limitedexperience in the field.

As such, there remains a need for a system, method and computer readablemedium capable of assisting the user with the oilfield simulationprocess utilizing information captured from prior reservoir simulations.

SUMMARY

Accordingly, the present disclosure describes an efficient processthrough which knowledge gleaned from prior reservoir simulations may becaptured and applied to future simulations with or without userinvolvement.

A plurality of reservoir simulation categories may be defined and storedto the database. In one embodiment, reservoir simulation categories maybe defined using information such as the type of the reservoir at issuein the simulation, the type of the simulation being conducted, theobjective(s) of the simulation, and/or the specific parameters utilizedduring the simulation. These information types may be utilized alone orin combination in order to categorize the simulation for futurereference.

In one embodiment, reservoir simulation data may be captured andanalyzed in order to identify process steps and/or workflows for eachcategory of reservoir simulation stored by the system. Identifiedworkflows may be cross-referenced by reservoir simulation category andapplied to future reservoir simulations.

In one embodiment, the system is capable of capturing reservoirsimulation data. In one embodiment, this may include capturing datarelating to user keystrokes, mouse movements, vocalcommands/conversations with other personnel, user eye movement, facialrecognition and/or any other user interaction with the system deemed tobe relevant to the workflow used during a reservoir simulation.

Upon starting a new reservoir simulation, the system may identify thecategory of the simulation at issue and query the database in order toidentify stored process steps and/or workflows applicable thereto. Thesystem may provide various query tools and graphic user interfaces (GUI)to facilitate the efficient retrieval of stored process steps and/orworkflows. Database query results may be displayed upon a GUI for reviewby the user or retrieved automatically from the database.

Retrieved workflows may be applied to the new reservoir simulation withor without human involvement. In one embodiment, the system may providean “automatic” and “assisted” mode selection option, whereby the usermay indicate their desired level of involvement. In this example, if theuser selects automatic mode, the system may automatically applyworkflows from previous simulations to the new simulation. In thisexample, if the user selects assisted mode, the system may providesuggestions and/or recommendations concerning how to proceed with thesimulation.

This summary is provided to introduce a selection of concepts in asimplified form that are further described herein. This summary is notintended to identify key or essential features of the claimed subjectmatter, nor is it intended to be used as an aid in determining the scopeof the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete appreciation of the invention and many of the attendantadvantages thereof will be readily obtained as the same becomes betterunderstood by reference to the following detailed description whenconsidered in connection with the accompanying drawings; it beingunderstood that the drawings contained herein are not necessarily drawnto scale and that the accompanying drawings provide illustrativeimplementations and are not meant to limit the scope of varioustechnologies described herein; wherein:

FIG. 1.1 is an example oilfield survey operation being performed by aseismic truck.

FIG. 1.2 is an example oilfield drilling operation being performed by adrilling tool suspended by a rig and advanced into the subterraneanformation.

FIG. 1.3 is an example oilfield wireline operation being performed by awireline tool suspended by the rig and into the wellbore of FIG. 1.2.

FIG. 1.4 is an example oilfield operation being performed by aproduction tool deployed from the rig and into a completed wellbore fordrawing fluid from the downhole reservoir into a surface facility.

FIG. 2.1 is an example oilfield seismic trace of the subterraneanformation of FIG. 1.1.

FIG. 2.2 is an example oilfield core sample of the example formationshown in FIG. 1.2.

FIG. 2.3 is an example oilfield well log of the subterranean formationof FIG. 1.3.

FIG. 2.4 is an example simulation decline curve of fluid flowing throughthe example subterranean formation of FIG. 1.4.

FIG. 3 is a schematic view, partially in cross section, of an exampleoilfield operation having a plurality of data acquisition toolspositioned at various locations along the oilfield operation forcollecting data from the subterranean formation.

FIG. 4 is an example schematic view of an oilfield operation having aplurality of wellsites for producing hydrocarbons from the subterraneanformation.

FIG. 5 is a flowchart diagram illustrating a reservoir simulationprocess of one example embodiment.

FIG. 6 is an example computer system that may be utilized in conjunctionwith one or more embodiments.

DETAILED DESCRIPTION

In the following description, numerous details are set forth to providean understanding of the present invention. However, it will beunderstood by those skilled in the art that the inventions describedherein may be practiced without these details and that numerousvariations or modifications from the described embodiments may bepossible.

The present disclosure describes embodiments of a method of conductingreservoir simulations, a computer readable medium for conductingreservoir simulations and a reservoir simulation system.

By way of background, FIGS. 1.1-1.4 illustrate simplified, schematicviews of oilfield (100) having subterranean formation (102) containingreservoir (104) therein in accordance with implementations of varioustechnologies and techniques described herein.

FIG. 1.1 illustrates a survey operation being performed by a surveytool, such as seismic truck (106.1), to measure properties of thesubterranean formation. In this example, the survey operation is aseismic survey operation for producing sound vibrations. In FIG. 1.1,sound vibrations (112) generated by source (110), reflects off horizons(114) in earth formation (116). A set of sound vibrations is received bysensors, such as geophone-receivers (118), situated on the earth'ssurface. The data received (120) is provided as input data to a computer(122.1) of a seismic truck (106.1), and responsive to the input data,computer (122.1) generates seismic data output (124). This seismic dataoutput may be stored, transmitted or further processed as desired, forexample, by data reduction.

FIG. 1.2 illustrates a drilling operation being performed by drillingtool (106.2) suspended by rig (128) and advanced into subterraneanformations (102) to form wellbore (136). Mud pit (130) is used to drawdrilling mud into the drilling tools via flow line (132) for circulatingdrilling mud down through the drilling tools, then up wellbore (136) andback to the surface. The drilling mud may be filtered and returned tothe mud pit.

A circulating system may be used for storing, controlling, or filteringthe drilling mud. The drilling tools are advanced into subterraneanformations (102) to reach reservoir (104). Each well may target one ormore reservoirs. The drilling tools may be adapted for measuringdownhole properties using logging while drilling tools. The loggingwhile drilling tools may also be adapted for taking core sample (133).

Computer facilities may be positioned at various locations about theoilfield (100) (e.g., the surface unit 134) and/or at remote locations.Surface unit (134) may be used to communicate with the drilling toolsand/or offsite operations, as well as with other surface or downholesensors. Surface unit is capable of communicating with the drillingtools to send commands to the drilling tools, and to receive datatherefrom. Surface unit may also collect data generated during thedrilling operation and produces data output (135), which may then bestored or transmitted.

Sensors (S), such as gauges, may be positioned about oilfield (100) tocollect data relating to various oilfield operations as describedpreviously. In this example, sensor (S) may be positioned in one or morelocations in the drilling tools and/or at rig (128) to measure drillingparameters, such as weight on bit, torque on bit, pressures,temperatures, flow rates, compositions, rotary speed, and/or otherparameters of the field operation. Sensors (S) may also be positioned inone or more locations in the circulating system.

Drilling tools (106.2) may include a bottom hole assembly (BHA) (notshown) near the drill bit (e.g., within several drill collar lengthsfrom the drill bit). The bottom hole assembly may include capabilitiesfor measuring, processing, and storing information, as well ascommunicating with the surface unit. The bottom hole assembly furthermay further include drill collars for performing various othermeasurement functions.

The data gathered by sensors (S) may be collected by the surface unitand/or other data collection sources for analysis or other processing.The data collected by sensors (S) may be used alone or in combinationwith other data. The data may be collected in one or more databasesand/or transmitted on or offsite. The data may be historical data, realtime data, or combinations thereof. The real time data may be used inreal time, or stored for later use. The data may also be combined withhistorical data or other inputs for further analysis. The data may bestored in separate databases, or combined into a single database.

Surface unit (134) may include transceiver (137) to allow communicationsbetween surface unit (134) and various portions of the oilfield (100) orother locations. The surface unit may also be provided with one or morecontrollers (not shown) for actuating mechanisms at the oilfield. Thesurface unit may then send command signals to the oilfield in responseto data received.

The surface unit may receive commands via transceiver (137) or mayitself execute commands to the controller. A processor may be providedto analyze the data (locally or remotely), make the decisions and/oractuate the controller. In this manner, the oilfield may be selectivelyadjusted based on the data that is collected and analyzed. Thistechnique may be used to optimize portions of the field operation, suchas controlling drilling, weight on bit, pump rates, or other parameters.These adjustments may be made automatically based on computer protocol,and/or manually by an operator. In some cases, well plans may beadjusted to select optimum operating conditions, or to avoid problems.

FIG. 1.3 illustrates a wireline operation being performed by wirelinetool (106.3) suspended by rig (128) and into wellbore (136) of FIG. 1.2.The wireline tool may be adapted for deployment into the wellbore forgenerating well logs, performing downhole tests and/or collectingsamples. The wireline tool may be used to provide another method andapparatus for performing a seismic survey operation. The wireline toolmay, for example, have an explosive, radioactive, electrical, oracoustic energy source (144) that sends and/or receives electricalsignals to surrounding subterranean formations (102) and fluids therein.

Wireline tool (106.3) may be operatively connected to, for example,geophones (118) and a computer (122.1) of a seismic truck (106.1) ofFIG. 1.1. Wireline tool (106.3) may also provide data to surface unit(134). Surface unit (134) may collect data generated during the wirelineoperation and may produce data output (135) that may be stored ortransmitted and subsequently analyzed. Wireline tool (106.3) may bepositioned at various depths in the wellbore (136) to provideinformation relating to the subterranean formation (102).

Sensors (S), such as gauges, may be positioned about oilfield (100) tocollect data relating to various field operations as describedpreviously. Sensors may be positioned in wireline tool (106.3) tomeasure downhole parameters which relate to, for example porosity,permeability, fluid composition and/or other parameters of the oilfieldoperation.

FIG. 1.4 illustrates a production operation being performed byproduction tool (106.4) deployed from a production unit or Christmastree (129) and into completed wellbore (136) for drawing fluid from thedownhole reservoirs into surface facilities (142). The fluid flows fromreservoir (104) through perforations in the casing (not shown) and intoproduction tool (106.4) in wellbore (136) and to surface facilities(142) via gathering network (146).

Sensors, such as gauges, may be positioned about oilfield (100) tocollect data relating to various field operations as describedpreviously. Sensors may be positioned in production tool (106.4) orassociated equipment, such as Christmas tree (129), gathering network(146), surface facility (142), and/or the production facility, tomeasure fluid parameters, such as fluid composition, flow rates,pressures, temperatures, and/or other parameters of the productionoperation.

Production may also include injection wells for added recovery. One ormore gathering facilities may be operatively connected to one or more ofthe wellsites for selectively collecting downhole fluids from thewellsite(s).

While FIGS. 1.2-1.4 illustrate tools used to measure data relating to anoilfield, it will be appreciated that the tools may be used inconnection with non-oilfield operations, such as gas fields, mines,aquifers, storage, or other subterranean facilities. Also, while certaindata acquisition tools are depicted, it will be appreciated that variousmeasurement tools capable of sensing parameters, such as seismic two-waytravel time, density, resistivity, production rate, etc., of thesubterranean formation and/or its geological formations may be used.Various sensors (S) may be located at various positions along thewellbore and/or the monitoring tools to collect and/or monitor thedesired data. Other sources of data may also be provided from offsitelocations.

FIGS. 2.1-2.4 are example graphical depictions of data collected by thetools of FIGS. 1.1-1.4. FIG. 2.1 depicts a seismic trace (202) of thesubterranean formation of FIG. 1.1 taken by survey truck (106.1). Theseismic trace measures a two-way response over a period of time. FIG.2.2 depicts a core sample (233) taken by the drilling tool (106.2). Thecore test may provide a graph of the density, resistivity, or otherphysical property of the core sample (233) over the length of the core.Tests for density and viscosity may be performed on the fluids in thecore at varying pressures and temperatures. FIG. 2.3 depicts a well log(204) of the subterranean formation of FIG. 1.3 taken by the wirelinetool (106.3). The wireline log typically provides a resistivitymeasurement of the formation at various depths. FIG. 2.4 depicts aproduction decline curve (206) of fluid flowing through the subterraneanformation of FIG. 1.4 taken by the production tool (106.4). Theproduction decline curve (206) may provide the production rate Q as afunction of time t.

The respective graphs of FIGS. 2.1-2.3 contain static measurements thatdescribe the physical characteristics of the formation. Thesemeasurements may be compared to determine the accuracy of themeasurements and/or for checking for errors. In this manner, the plotsof each of the respective measurements may be aligned and scaled forcomparison and verification of the properties.

FIG. 2.4 provides a dynamic measurement of the fluid properties throughthe wellbore. As the fluid flows through the wellbore, measurements aretaken of fluid properties, such as flow rates, pressures, composition,etc. As described below, the static and dynamic measurements may be usedto generate models of the subterranean formation to determinecharacteristics thereof.

FIG. 3 is a schematic view, partially in cross section of an oilfield(300) having data acquisition tools (302A), (302B), (302C), and (302D)positioned at various locations along the oilfield for collecting dataof a subterranean formation (304). The data acquisition tools(302A-302D) may be the same as data acquisition tools of FIG. 1,respectively. In this example, the data acquisition tools (302A-302D)may generate data plots or measurements (308A-308D), respectively.

Data plots (308A-308D) are examples of static data plots that may begenerated by the data acquisition tools (302A-302D), respectively.Static data plot (308A) is a seismic two-way response time and may bethe same as the seismic trace (202) of FIG. 2.1. Static plot (308B) iscore sample data measured from a core sample of the formation (304),similar to the core sample (233) of FIG. 2.2. Static data plot (308C) isa logging trace, similar to the well log (204) of FIG. 2.3. Data plot(308D) is a dynamic data plot of the fluid flow rate over time, similarto the graph (206) of FIG. 2.4. Other data may also be collected, suchas historical data, user inputs, economic information, other measurementdata, and other parameters of interest.

The subterranean formation (304) has a plurality of geologicalstructures (306A-306D). In this example, the formation has a sandstonelayer (306A), a limestone layer (306B), a shale layer (306C), and a sandlayer (306D). A fault line (307) extends through the formation. Thestatic data acquisition tools may be adapted to measure the formationand detect the characteristics of the geological structures of theformation.

While a specific subterranean formation (304) with specific geologicalstructures are depicted, it will be appreciated that the formation maycontain a variety of geological structures. Fluid may also be present invarious portions of the formation. Each of the measurement devices maybe used to measure properties of the formation and/or its underlyingstructures in order to generate oilfield data. While each acquisitiontool is shown as being in specific locations along the formation, itwill be appreciated that one or more types of measurement may be takenat one or more location across one or more oilfields or other locationsfor comparison and/or analysis.

The data collected from various sources, such as the data acquisitiontools of FIG. 3, may then be evaluated using one or more datavisualization applications. Seismic data displayed in the static dataplot (308A) from the data acquisition tool (302A) may be used by ageophysicist to determine characteristics of the subterranean formation(304). Core data shown in static plot (308B) and/or log data from thewell log (308C) may be used by a geologist to determine variouscharacteristics of the geological structures of the subterraneanformation (304). Production data from the production graph (308D) may beused by the reservoir engineer to determine fluid flow and reservoircharacteristics.

FIG. 4 illustrates an example oilfield (400) for performing oilfieldoperations. In this example, the oilfield has a plurality of wellsites(402) operatively connected to a central processing facility (454). Partor all of the oilfield may be on land and/or sea. Also, while a singleoilfield with a single processing facility and a plurality of wellsitesis depicted, any combination of one or more oilfields, one or moreprocessing facilities and one or more wellsites may be present.

Each wellsite (402) may have equipment that forms a wellbore (436) intothe earth. The wellbores extend through subterranean formations (406)including reservoirs (404). These reservoirs (404) contain fluids, suchas hydrocarbons. The wellsites draw fluid from the reservoirs and passthem to the processing facilities via surface networks (444). Thesurface networks (444) may have tubing and control mechanisms forcontrolling the flow of fluids from the wellsite to the processingfacility (454).

Referring to FIG. 5, the present disclosure describes a system, method,and computer readable medium for conducting reservoir simulations.Specifically, the present disclosure describes an efficient processthrough which knowledge gleaned from prior reservoir simulations may becaptured and applied to future simulations.

In one embodiment, one or more computer databases (500) may be utilizedfor storing reservoir simulation data (505) relating to one or moreoilfield operations (510). A plurality of reservoir simulationcategories may be defined and stored to the database, as illustrated byBox (515). In one embodiment, reservoir simulation categories may bedefined using information such as the type of the reservoir at issue inthe simulation, the type of the simulation being conducted, theobjective(s) of the simulation, and/or the specific parameters utilizedduring the simulation. These information types may be utilized alone orin combination in order to categorize the simulation for futurereference.

The reservoir simulation categories described herein may be utilized tostore and/or retrieve process steps and/or workflows pertaining tocertain type(s) of reservoir simulations for future use. In oneembodiment, the reservoir type may include information concerning theproperties of the reservoir. In this example, the properties of thereservoir may include information such as the fluids present, rockproperties, porosity information, permeability information, oil content,gas content, water saturation, temperature gradients, pressuregradients, etc. This information may be reflected by the system usingone or more codes. For example, a fluid type code may be used toindicate fluid types, porosity type codes may be used to indicateporosity types, an average net pay code may be used to indicate theamount of oil present in the reservoir, etc.

In one embodiment, geological characteristics of the reservoir may beutilized in order to categorize the reservoir simulation according toreservoir type. For example, the geological characteristics of thereservoir may include information such as the geometry of the reservoir,structural/stratigraphic characteristics of the reservoir (faults, etc),and/or depositional/sedimental characteristics of the reservoir(alluvial-fan, fluvial, Eolian, delta systems, barrier bars, shelf,slope, basinal, etc).

Geological information concerning the reservoir may be reflected by thesystem using one or more codes. For example, a lithology code may beused to indicate the relative lithology of the reservoir, a tectonicscode may be utilized to indicate the relative tectonic characteristicsof the reservoir, etc.

In one embodiment, the simulation type may indicate the type ofsimulation at issue. In this example, the simulation type may indicatewhether the simulation is a black oil, compositional, thermal, etc.,type of simulation and/or a history matching, well locationoptimization, production optimization, enhanced oil recovery, etc., typeof simulation. The objective(s) of the simulation may also be utilizedin order to categorize the reservoir simulation. For example, in thecontext of a history matching simulation, the objective of thesimulation may be to obtain a matching result with respect to certainparameters, such as the oil rate, the water rate, etc.

In one embodiment, simulation parameters may also be utilized in orderto categorize the reservoir simulation. Simulation parameters mayinclude anything of interest to the simulation, including the type ofoptimization algorithm(s), the type of permeability curve(s), etc. Forexample, in a reservoir simulation having a sloped geologicalenvironment, simulation parameters such as the slope thickness, arealdistribution, vertical distribution, etc., may be utilized. In anexample reservoir having a fluvial geological environment, reservoirsimulation parameters such as the sinuosity of the channel, the channelratio, etc, may be utilized. For an example reservoir containing anaquifer, simulation parameters may include aquifer related parameters,such as aquifer strength, aquifer type, aquifer location (side, bottom),etc.

In one embodiment, reservoir simulation data may be captured andanalyzed in order to identify process steps and/or workflows for eachcategory of reservoir simulation stored by the system, as illustrated byBoxes (520) and (525) of FIG. 5. In one embodiment, a workflow mayinclude a plurality of reservoir simulation process steps. Identifiedworkflows may be cross-referenced by reservoir simulation category andapplied to future reservoir simulations.

In one embodiment, the system is capable of capturing reservoirsimulation data. In one embodiment, this may include capturing datarelating to user keystrokes, mouse movements, vocalcommands/conversations with other personnel, user eye movement and/orany other user interaction with the system deemed to be relevant to theworkflow used during a reservoir simulation.

Reservoir simulation data may be gleaned from previously storedreservoir simulations (such as those stored upon database (500)) and/orcaptured in real time (or near real time) during reservoir simulationsperformed by one or more example users (530) using example computer(535).

Direct commands made by the user (via keystroke, mouse movement, verbalcommands, etc) may be captured and stored by the system. For example, ifthe user desires to enter a direct statement such as “for reservoir type“A” I don't want a pressure value greater than 200 psi,” he or she canenter the command via the keyboard or speak the appropriate command. Thecommand may then be captured by the system and applied to the rest ofhis or her simulation. Further, any direct commands may be stored foruse with subsequent simulations having similar reservoircharacteristics.

In one embodiment, a computer utilized by a user during a reservoirsimulation may be equipped with an eye tracking module (540) capable oftracking and recording the user's eye movements during a simulation. Theeye tracking module may include hardware, software, or a combinationthereof. User eye movements during the simulation may becross-referenced with other actions taken by the user (keystrokes, mousemovement, etc.) along with events occurring upon the computer screen inorder to capture the process steps taken by the user during thesimulation and apply the process steps (or workflows) to futuresimulations having similar characteristics.

Consider a situation where a user is looking at a visualization of areservoir upon his or her computer screen during a history matchingsimulation involving a reservoir having an aquifer. In this example, theuser is likely to look at certain portions of the displayed reservoir inorder to access the parameters (or ranges of parameters) that he or sheneeds to use during the simulation. In this example, the user may decideto generate a graphical display of the pressure field around the aquiferin order to access the impact of the aquifer upon the pressuredistribution of the reservoir.

In this example, the eye tracking functionality of the system is capableof capturing and cross referencing the eye movements of the user withevents on screen in order to capture the workflow used by the userduring the simulation. Thus, in this example, the system utilizes eyetracking technology to track the process steps taken by the user inconnection with a reservoir simulation involving a reservoir having anaquifer and a history matching simulation type.

The eye tracking functionality described herein may be applied to theresults portion of the simulation as well. Consider a situation wherethe user has completed the simulation and is reviewing the results uponhis or her computer screen. The user may look at certain portions of thecomputer screen in order to ascertain the success (or lack thereof) ofthe simulation. In this example, the eye tracking functionality of thesystem is capable of capturing and cross referencing the eye movementsof the user with events on screen in order to capture the workflow usedby the user during the “results phase” of the simulation.

In one embodiment, data gleaned from eye tracking may be utilized inorder to generate one or more maps (not shown) illustrating theimportant portions of the displayed data during a reservoir simulation.In the simplified example above, a first map could be generated toindicate the relative importance of the displayed data relating thepressure profile around the aquifer and a second map could be generatedto indicate the relative importance of the simulation results.

In one embodiment, a color scheme could be utilized to denote areas ofuser eye concentration upon the screen. For example, areas of highconcentration could be denoted with a red color, areas of middleconcentration could be denoted with a yellow color, while areas with alow concentration could be denoted with a green color. Data gleaned fromeye tracking may also be utilized to highlight one or more portions ofthe display screen during subsequent simulations in order to indicatetheir relative importance.

In one embodiment, audio capture functionality capable of tracking andrecording the user's verbal commands and/or conversations during asimulation may be utilized. In one embodiment, the user's computer maybe equipped with audio capture hardware, such as a microphone (545) andsoftware having Natural Language Processing (NLP) capability.

User conversations and/or voice commands during the simulation may becross-referenced with other actions taken by the user (keystrokes, mousemovement, etc.) along with events upon the computer screen in order tocapture the process steps taken by the user during the simulation andapply the process steps (or workflows) to future simulations havingsimilar characteristics.

Consider the above example where a user is conducting a history matchingof a reservoir simulation model with an aquifer. In this example, audiocommands made by the user during the simulation may be captured by themicrophone and processed by the NLP software. Further, voice commandsmade by other personnel (such as a supervisor discussing the simulationwith the user) may be recorded and used to identify simulation processsteps and/or workflows.

Consider an example where the user discusses a field pressure simulationparameter with his or her supervisor during a reservoir simulation. Inthis example, the system may capture the conversation and crossreference it with the actions taken by the user subsequent to theconversation in order to identify appropriate process steps and/orworkflows relating to the field pressure parameter given thecharacteristics of the simulation.

In one embodiment, the system (in conjunction with the NLP software) maygenerate IF/THEN rules/statements utilizing the captured audioinformation for use during future simulations having similarcharacteristics. For example, if the system captures a conversationbetween the user and their supervisor where the user asks if a wellinjection pressure of 100 psi is appropriate for a certain type ofreservoir and the supervisor says “No, you need to increase the wellinjection pressure to at least 200 psi for that type of reservoir,” thesystem may record this exchange and convert it to IF/THENrules/statements indicating that 200 psi or greater would be preferredfor future simulations having similar characteristics.

Another example of verbal communication involving a reservoir having anaquifer with excessive water production could read along the lines ofthe following: “Do you have an aquifer defined on the data deck?Normally the rule of thumb is to have an aquifer 20 to 30 times biggerthan the reservoir volume you have . . . check the relationshipaquifer-reservoir you have. If this is too high (bigger than 30 times)aquifer will be very strong and you will have a lot of water production.Another thing you can try is to increase porosity between the water zoneand the wells. As you have more rock volume, it will take more time forthe water to fill the cells and therefore to breakthrough in the wells.”

In this example, the system may capture the conversation and analyze itto identify the important aspect(s) of the conversation. In thisexample, the system may identify that the aquifer should be 20 to 30times bigger than the reservoir volume and that this information shouldbe considered when defining aquifer parameters. Further, the system mayautomatically fashion IF/THEN rules/statements from the capturedconversation:

1) IF we have water production above “X” amount, THEN the aquifer sizemight be the problem. THEN reduce aquifer size if you get excessivewater production.

2) IF point #1 does not solve the problem, THEN increase porositybetween water zone and one or more wells.

In one embodiment, facial recognition software may be used (inconnection a suitable camera or other video device) to identify eachuser providing input on a reservoir simulation. This feature allows thesystem to track where captured data comes from and provide thatinformation to subsequent users where appropriate.

In the field pressure example above, the facial recognitionfunctionality allows the system to identify who is speaking in thecaptured audio conversation and access their skills/experience prior toinclusion in the identified workflow(s). The system may provide thisinformation to future users in connection with their simulation, i.e.,“Supervisor John Doe indicated that a field pressure of greater than 200psi should be utilized in connection with a history matching simulationfor a reservoir of category ‘A’ having at least one aquifer.”

In one embodiment, each process step and/or workflow may be associatedwith one or more reservoir simulation categories and stored to thedatabase, as illustrated by Boxes (550) and (555) of FIG. 5. This may beaccomplished using metadata or other suitable data storage conventions.This feature allows stored process steps and/or workflows to be matchedto a particular simulation category, retrieved via query tool(s) andapplied to future reservoir simulations.

The system may also track run-time options, convergence and speed-upmodifications and/or any errors encountered during the simulation(s). Agoodness of simulation measure may be considered in accessing theresults of the captured simulation. For example, in a history matchingstudy, the goodness of simulation may utilize the misfit value of aproduction data parameter. In this example, the misfit value may be thedifference between simulated and field observation(s) for one or moreoutputs of the reservoir model. In a thermal simulation, the goodness ofsimulation may utilize values such as the steam oil ratio or thetemperature profile around a well. If the user makes any changes toimprove the goodness of simulation, the action (e.g. changing the numberor position of inflow control devices) may be recorded along with thegoodness of simulation value and applied to future simulations asappropriate.

The system may utilize one or more learning algorithms during thereservoir simulation data capture process. In one embodiment, supervisedand unsupervised learning algorithms may be utilized alone or oncombination. In one embodiment, a supervised learning algorithm mayutilize label data as a training data set whereas an unsupervisedlearning algorithm would not require the use of such data.

Upon starting a new reservoir simulation, the system may identify thecategory of the simulation at issue and query the database in order toidentify stored process steps and/or workflows applicable thereto, asillustrated by Boxes (560), (565) and (570) of FIG. 5. The system mayprovide various query tools and graphic user interfaces to facilitatethe efficient retrieval of stored process steps and/or workflows.Database query results may be displayed upon a GUI for review by theuser or retrieved automatically from the database, as illustrated by Box(575) of FIG. 5. The system may be pre-programmed with defaultthresholds indicating whether process steps and/or workflow(s) fromprior simulation(s) substantially match the new simulation. In oneembodiment, such thresholds may be altered according to userpreferences.

In one embodiment, a ranking feature may be utilized whereby the systemranks the retrieved process steps/workflows according to the number ofsimilarities between the reservoir at issue and the reservoirs of thestored workflows. For example, the system may retrieve multiple sets ofstored workflows and rank them by a degree of similarity with respect toreservoir type, simulation type, simulation objectives and simulationparameters.

In this example, the degree of similarity may be determined according tohow many reservoir categories, simulation categories, and/or parametercategories the current simulation has in comparison to the reservoirs ofthe stored workflows. In one embodiment, the system may use a GUI toillustrate the retrieved workflows and provided details as to theirprevious application. For example, the GUI may show a list of retrievedworkflows ranked according to reservoir similarity, where the workflowwas used previously, etc., such that the user may select which workflowhe or she wishes to apply to their current simulation. Further, thesystem may provide a GUI through which the user may indicate that he orshe wishes to emphasize a particular type of reservoir, simulationand/or parameter type.

Upon reviewing the query results, the user may select one or more of theidentified process steps and/or workflows associated with the simulationat issue. He or she may also be given the option to change the order orparameters of the displayed process steps as desired. Upon selection bythe user, the selected process steps and/or workflows may be applied tothe reservoir simulation and the results displayed to the user, asillustrated by Box (580) of FIG. 5. In one embodiment, the system allowsthe user to amend and/or revise the process steps and/or workflows to beperformed via a suitable graphic user interface. In some cases, this mayrequire entry of additional process steps and/or workflows, such ascustom operations, into the system.

In one embodiment, the database may include historical informationregarding each process step or workflow. Historical information mayinclude information such as when and where stored processsteps/workflows have been used, the number of times they have been used,the simulation categories they have been used with during pastsimulations, etc. Historical information may be stored upon the databaseand presented to the user when he or she interacts with the system. Inone embodiment, a balloon or box (not shown) may be displayed to theuser adjacent to a process step and/or workflow. This feature helps theuser determine the applicability and/or reliability of the processstep(s) and/or workflows in question for their particular simulation.

Retrieved workflows may be applied to the new reservoir simulation withor without human involvement. In one embodiment, the system may providean “automatic” and “assisted” mode selection option, whereby the usermay indicate their desired level of involvement. In this example, if theuser selects automatic mode, the system may automatically applyworkflows from previous simulations to the new simulation. This featuremay involve automatic population of one or more of the parameter fieldsof the new simulation.

In one embodiment, the user may refine reservoir simulations using astyling interface (585). In one embodiment, a unique styling interfacemay be provided for each reservoir simulation category in order to allowthe user to adjust how the simulation is displayed.

In one embodiment, user selections and/or styling preferences may bestored for later projects. For example, if a user has selectedparameters and styling preferences for a particular reservoir simulationcategory, the system may store preference information for the userand/or project in question and apply it to later sessions. In oneembodiment, stored selections and/or styling data may be stored andapplied to subsequent sessions according to reservoir simulationcategory, such that the user's next encounter with a particular type ofreservoir simulation may automatically be populated with the user'spreferences.

The system may provide customization options whereby the user may amenddefault process steps and/or workflows by entering and/or importingcustom preferences and/or customized reservoir simulation types. In oneembodiment, this may be accomplished using one or more customizationscreens (not shown). This feature may also be used to allow the user toenter custom process steps and/or workflows so that highly trained usersmay tailor the system to their specifications.

The system, method and computer readable medium described herein may beutilized in conjunction with any suitable reservoir simulation types andthe inventions described herein are not limited to use with the examplereservoir simulation types or example process steps and/or workflows.Further, the inventions described herein may be used at any phase of anoilfield operation including, but not limited to, during theinterpretation of seismic data, during modeling of formationalcharacteristics or reservoir properties (including surface modeling),and/or during operational monitoring and analysis activities.

The methods described herein may be implemented on any suitable computersystem capable of processing electronic data. FIG. 6 illustrates onepossible configuration of a computer system (590) that may be utilized.Computer system(s), such as the example system of FIG. 6, may runprograms containing instructions, that, when executed, perform methodsaccording to the principles described herein. Furthermore, the methodsdescribed herein may be fully automated and able to operatecontinuously, as desired.

The computer system may utilize one or more central processing units(595), memory (600), communications or I/O modules (605), graphicsdevices (610), a floating point accelerator (615), and mass storagedevices such as tapes and discs (620). Storage device (620) may includea floppy drive, hard drive, CD-ROM, optical drive, or any other form ofstorage device. In addition, the storage devices may be capable ofreceiving a floppy disk, CD-ROM, DVD-ROM, disk, flash drive or any otherform of computer-readable medium that may contain computer-executableinstructions.

Further, communication device (605) may be a modem, network card, or anyother device to enable communication to receive and/or transmit data. Itshould be understood that the computer system (590) may include aplurality of interconnected (whether by intranet or Internet) computersystems, including without limitation, personal computers, mainframes,PDAs, cell phones and the like.

It should be understood that the various technologies described hereinmay be implemented in connection with hardware, software or acombination of both. Thus, various technologies, or certain aspects orportions thereof, may take the form of program code (i.e., instructions)embodied in tangible media, such as floppy diskettes, CD-ROMs, harddrives, or any other machine-readable storage medium wherein, when theprogram code is loaded into and executed by a machine, such as acomputer, the machine becomes an apparatus for practicing the varioustechnologies.

In the case of program code execution on programmable computers, thecomputing device may include a processor, a storage medium readable bythe processor (including volatile and non-volatile memory and/or storageelements), at least one input device, and at least one output device.One or more programs that may implement or utilize the varioustechnologies described herein may use an application programminginterface (API), reusable controls, and the like.

Such programs may be implemented in a high level procedural or objectoriented programming language to communicate with a computer system.However, the program(s) may be implemented in assembly or machinelanguage, if desired. In any case, the language may be a compiled orinterpreted language, and combined with hardware implementations.

The computer system (590) may include hardware capable of executingmachine readable instructions, as well as the software for executingacts that produce a desired result. In addition, computer system (590)may include hybrids of hardware and software, as well as computersub-systems.

Hardware may include at least processor-capable platforms, such asclient-machines (also known as personal computers or servers), andhand-held processing devices (such as smart phones, personal digitalassistants (PDAs), or personal computing devices (PCDs), for example).Further, hardware may include any physical device that is capable ofstoring machine-readable instructions, such as memory or other datastorage devices. Other forms of hardware include hardware sub-systems,including transfer devices such as modems, modem cards, ports, and portcards, for example.

Software includes any machine code stored in any memory medium, such asRAM or ROM, and machine code stored on other devices (such as floppydisks, flash memory, or a CD ROM, for example). Software may includesource or object code, for example. In addition, software encompassesany set of instructions capable of being executed in a client machine orserver.

A database may be any standard or proprietary database software, such asOracle, Microsoft Access, SyBase, or DBase II, for example. The databasemay have fields, records, data, and other database elements that may beassociated through database specific software. Additionally, data may bemapped. Mapping is the process of associating one data entry withanother data entry. For example, the data contained in the location of acharacter file can be mapped to a field in a second table. The physicallocation of the database is not limiting, and the database may bedistributed. For example, the database may exist remotely from theserver, and run on a separate platform.

Further, the computer system may operate in a networked environmentusing logical connections to one or more remote computers. The logicalconnections may be any connection that is commonplace in offices,enterprise-wide computer networks, intranets, and the Internet, such aslocal area network (LAN) and a wide area network (WAN). The remotecomputers may each include one or more application programs.

When using a LAN networking environment, the computer system may beconnected to the local network through a network interface or adapter.When used in a WAN networking environment, the computer system mayinclude a modem, wireless router or other means for establishingcommunication over a wide area network, such as the Internet.

The modem, which may be internal or external, may be connected to thesystem bus via the serial port interface. In a networked environment,program modules depicted relative to the computer system, or portionsthereof, may be stored in a remote memory storage device.

Although the invention has been described with reference to specificembodiments, this description is not meant to be construed in a limitedsense. Various modifications of the disclosed embodiments, as well asalternative embodiments of the invention, will become apparent topersons skilled in the art upon reference to the description of theinvention. It is, therefore, contemplated that the appended claims willcover such modifications that fall within the scope of the invention.

What is claimed is:
 1. A computer implemented method for conductingreservoir simulations comprising: identifying one or more workflowsutilized in connection with one or more reservoir simulations; storingthe identified workflows to a computer database; and applying at leastone of the identified workflows to a subsequent reservoir simulation. 2.The computer implemented method of claim 1, wherein the workflowscomprise a plurality of reservoir simulation process steps.
 3. Thecomputer implemented method of claim 1, wherein one or more of theworkflows are identified using voice recognition or eye tracking.
 4. Thecomputer implemented method of claim 1, wherein one or more of theidentified workflows are associated with one or more reservoirsimulation categories.
 5. The computer implemented method of claim 1,further comprising: determining a reservoir simulation categoryassociated with the identified workflow and the subsequent reservoirsimulation; and wherein the reservoir simulation category of theidentified workflow substantially matches the reservoir simulationcategory of the subsequent reservoir simulation.
 6. The computerimplemented method of claim 5, wherein the reservoir simulation categoryfurther comprises a reservoir type, a simulation type, and one or moresimulation parameters.
 7. The computer implemented method of claim 6,wherein the reservoir type further comprises fluid, porosity andpermeability properties of the reservoir.
 8. The computer implementedmethod of claim 6, wherein the reservoir type further comprises aplurality of geological properties of the reservoir.
 9. The computerimplemented method of claim 6, wherein the simulation type comprises ahistory matching simulation or a thermal simulation.
 10. The computerimplemented method of claim 1, wherein at least one of the identifiedworkflows are applied to the subsequent reservoir simulation byproviding recommendations to a user.
 11. The computer implemented methodof claim 1, wherein at least one of the identified workflows are appliedto the subsequent reservoir simulation automatically without userintervention.
 12. A reservoir simulation system comprising: a processoroperative to: identify one or more workflows utilized in connection withone or more reservoir simulations; store the identified workflows to acomputer database; and apply at least one of the identified workflows toa subsequent reservoir simulation, wherein at least one reservoirsimulation category associated with the identified workflowsubstantially matches at least one reservoir simulation categoryassociated with the subsequent reservoir simulation.
 13. The reservoirsimulation system of claim 12, wherein one or more of the workflows areidentified using voice recognition or eye tracking.
 14. The reservoirsimulation system of claim 12, wherein the reservoir simulationcategories further comprise reservoir type, simulation type, andsimulation parameters.
 15. The reservoir simulation system of claim 12,wherein the identified workflows are applied to the subsequent reservoirsimulation by providing recommendations to a user.
 16. The reservoirsimulation system of claim 12, wherein the identified workflows areapplied to the subsequent reservoir simulation automatically withoutuser intervention.
 17. A non-transitory computer readable medium forconducting reservoir simulations comprising instructions which, whenexecuted, cause a computing device to: identifying one or more workflowsutilized in connection with one or more reservoir simulations; storingthe identified workflows to a computer database; determining a reservoirsimulation category associated with the identified workflow and asubsequent reservoir simulation; and applying at least one of theidentified workflows to a subsequent reservoir simulation, wherein thereservoir simulation category of the identified workflow substantiallymatches the reservoir simulation category of the subsequent reservoirsimulation.
 18. The computer readable medium of claim 17, wherein thereservoir simulation category further comprises a reservoir type, asimulation type, and one or more simulation parameters.
 19. The computerreadable medium of claim 18, wherein the reservoir type furthercomprises a plurality of geological properties of the reservoir.
 20. Thecomputer readable medium of claim 18, wherein the simulation typecomprises a history matching simulation or a thermal simulation.